Disease trajectories in hospitalized COVID-19 patients are predicted by clinical and peripheral blood signatures representing distinct lung pathologies

Abstract

SummaryLinking clinical biomarkers and lung pathology still is necessary to understand COVID-19 pathogenesis and the basis of progression to lethal outcomes. Resolving these knowledge gaps enables optimal treatment approaches of severe COVID-19. We present an integrated analysis of longitudinal clinical parameters, blood biomarkers and lung pathology in COVID-19 patients from the Brazilian Amazon. We identified core signatures differentiating severe recovered patients and fatal cases with distinct disease trajectories. Progression to early death was characterized by rapid and intense endothelial and myeloid activation, presence of thrombi, mostly driven by SARS-CoV-2+macrophages. Progression to late death was associated with systemic cytotoxicity, interferon and Th17 signatures and fibrosis, apoptosis, and abundant SARS-CoV-2+epithelial cells in the lung. Progression to recovery was associated with pro-lymphogenic and Th2-mediated responses. Integration of ante-mortem clinical and blood biomarkers with post-mortem lung-specific signatures defined predictors of disease progression, identifying potential targets for more precise and effective treatments.

Spatially resolved single-cell atlas of the lung in fatal Covid19 in an African population reveals a distinct cellular signature and an interferon gamma dominated response

“…To give cellular context to the histopathological features we made tissue microarrays, identifying 130 representative regions of interest containing specific pathological lesions or normal lung areas (9 Covid, 3 LRTD, 2 Non-LRTD cases). Tissue samples were analysed by IMC using a 39 metal-conjugated antibody panel (Supplemental information) that we previously optimised for staining in a Brazil cohort 13 , an anti-SARS-CoV2 Spike (SARS-CoV2-S) antibody validated in lung tissue 13,30 . After cell-segmentation and quality control, we annotated 76,369 cells.…”

“…Then, two additional pathologists (V.H., C.A. ), blinded to diagnosis, scored the lung pathology in all sixteen patients using more detailed semi-quantitative criteria developed by us previously 13 . Within our Covid19 cases, type II pneumocyte hyperplasia, vascular congestion, syncytia, granulation of tissue and lymphocyte infiltration were all significantly more common and severe than in the non-Covid19 LRTD group; in contrast neutrophils were more numerous in LRTD cases (Extended Data Fig.1a).…”

“…Unfortunately, a lack of international consensus criteria for assessing Covid19 lung pathology, and of studies with systematic scoring, prevented quantitative comparison with other cohorts to assess similarities and differences. Therefore, we compared proportions of different pulmonary lesion types with a study that combined cohorts from Europe and the USA 21 , and with our published Brazilian cohort 13 (Fig.1c). Acute alveolar changes, defined by neutrophil infiltration and fibrin-deposition were more frequent in the Malawi and Brazil cohorts than the USA cohort.…”

“…After cell assignment, cells labelled as “other” or “unknown” were filtered out from downstream analysis, the annotated data object was subset into the major cell types identified, i.e., macrophages, neutrophils, lymphoid, vascular, epithelial and stromal and Phenograph Louvain clustering (with 200 nearest neighbors) 53 was performed for each cell population separately using a small set of specific lineage marker and functional proteins, as previously described 13 . The finer cell type annotation was used to evaluate the frequency and absolute counts of cell types across clinical groups, histopathological lesions and HIV status.…”

“…Single-cell data from lung tissue facilitated identification of specific immunomodulatory targets 3,7–12 . Apart from our high-dimensional imaging study from a Brazilian cohort 13 these data are, thus far, exclusively from populations in Northern hemisphere, similar to most clinical trial data validating their efficacy. For future waves or epidemics of SARS-CoV2 or related viruses, this knowledge gap needs to be addressed.…”